Abishek Flashcards
(21 cards)
What is Business Intelligence (BI)?
Business Intelligence (BI) is the practice of using technologies and methods to collect, analyze, and visualize business data to support informed decision-making.
It transforms raw data into actionable insights to answer not just what happened, but also:
Why it happened
What might happen
What should we do
BI vs Traditional Data Analysis
Feature | Traditional Analysis | Business Intelligence |
| ———— | ——————– | ————————— |
| Focus | Past only | Past, present & future |
| Tools | Excel, SPSS | Tableau, Power BI, SQL |
| Method | Manual | Automated, real-time |
| Output | Static reports | Dashboards, visual insights |
| Key Question | What happened? | What, Why, What’s next? |
How does Facebook use Business Intelligence in practice?
Facebook collects your behavior data (likes, clicks, scroll time)
It analyzes your patterns to predict what you want to see
It visualizes performance for advertisers
It automates content recommendations
✅ This is not just reporting — it’s intelligent, real-time BI in action
📚 What is Big Data?
Big Data refers to extremely large, fast, and diverse datasets that are too complex for traditional tools (like Excel) to process.
It allows businesses to make real-time, predictive, and data-driven decisions using advanced analytics.
What are the 4 Vs of Big Data?
V | Meaning | Example |
| ———— | —————————- | ——————————– |
| Volume | Huge data size | Social media, online purchases |
| Velocity | Speed of incoming data | Stock prices, IoT sensors |
| Variety | Different formats | Text, video, audio, spreadsheets |
| Veracity | Data quality and reliability | Inaccurate entries, duplicates |
How do companies use Big Data?
Netflix: Tracks viewing behavior to recommend and create content
Amazon: Uses click and purchase data for real-time recommendations
Healthcare/IoT: Monitors patient vitals via wearable sensors
Finance: Detects fraud in real-time using fast data flows
What is a data warehouse?
A data warehouse is a central storage system where data from different sources (e.g., sales, finance, CRM) is collected, cleaned, and organized to support business intelligence (BI) tools and decision-making.
What does ETL stand for in data warehousing?
Step | Description |
| ————- | —————————————- |
| Extract | Pulls data from various sources |
| Transform | Cleans, formats, and unifies the data |
| Load | Sends structured data into the warehouse |
How does a data warehouse support Business Intelligence?
Combines all business data in one place
Ensures consistency and accuracy
Enables dashboards, reports, and analytics
Supports faster, smarter, real-time decisions
Powers tools like Power BI, Tableau, and SQL
What is data mining?
Data mining is the process of using technology, statistics, and algorithms to discover hidden patterns, trends, and relationships in large datasets.
✅ It helps businesses predict behavior, detect risks, and generate insights.
What are 4 common data mining techniques?
Technique | What It Does | Example |
| ——————— | ————————— | ——————————– |
| Classification | Sorts data into categories | Spam vs. not spam |
| Regression | Predicts a continuous value | Future sales |
| Clustering | Groups similar data | Customer segmentation |
| Association Rules | Finds linked behavior | “Customers who buy X also buy Y” |
How is data mining used in real businesses?
Netflix → Content recommendations
Amazon → Product suggestions
Banks → Fraud detection
Healthcare → Disease risk identification
Marketing → Customer churn prediction
📝 What is text analytics?
Text analytics is the process of analyzing unstructured text data (like reviews, emails, or social media posts) to extract useful insights.
It helps identify:
Key topics and keywords
Sentiment (positive/negative/neutral)
Common themes and customer feedback
🌐 What is web analytics?
Web analytics tracks and analyzes how users interact with a website.
It measures:
Page visits
Clicks
Bounce rate
User behavior flow
✅ Helps businesses improve content, design, and user experience.
📊 How do companies use text and web analytics?
Text Analytics:
→ Improve customer service by analyzing support tickets
→ Guide product changes from review feedback
Web Analytics:
→ Optimize landing pages with high bounce rates
→ Track user journeys to improve conversion rates
→ Refine digital marketing campaigns
🧠 What is a business analytics strategy?
It’s a long-term plan that aligns a company’s goals with the collection, analysis, and use of data.
It ensures that data and tools are used to support smart decisions, improve performance, and drive growth.
Why do companies need a business analytics strategy?
Aligns analytics with business objectives
Helps avoid wasting time on irrelevant data
Promotes data-driven decisions across teams
Builds a roadmap for tools, training, and KPIs
Ensures ethical and accurate use of data
What are the key elements of a business analytics strategy?
Business Goals – Clear objectives
Data Strategy – What data, from where?
Tools & Technology – Power BI, Tableau, Python, etc.
People & Skills – Trained staff, analysts, decision-makers
Types of Analytics – Descriptive, diagnostic, predictive, prescriptive
Governance & Ethics – Privacy, accuracy, compliance
KPIs & Metrics – How success is measured
📈 What is the Gartner Hype Cycle?
It’s a model that shows how new technologies evolve over time, from early excitement to realistic adoption.
It helps businesses decide when and how to invest in emerging tech based on expectation vs. reality.
What are the 5 stages of the Gartner Hype Cycle?
Innovation Trigger – New tech appears, media attention starts
Peak of Inflated Expectations – Hype explodes, unrealistic hopes
Trough of Disillusionment – Reality hits, disappointment sets in
Slope of Enlightenment – Realistic applications begin to work
Plateau of Productivity – Tech matures, delivers real value
💼 Why should companies care about the Gartner Hype Cycle?
Avoid investing in overhyped, immature tech
Focus on real-world use cases
Improve timing of adoption and budget planning
Understand technology readiness for your strategy
